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Record W2159827819 · doi:10.1364/oe.22.027553

Decision-aided sampling frequency offset compensation for reduced-guard-interval coherent optical OFDM systems

2014· article· en· W2159827819 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOptics Express · 2014
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsMcGill University
Fundersnot available
KeywordsGuard intervalOrthogonal frequency-division multiplexingCyclic prefixComputer sciencePolarization-division multiplexingQuadrature amplitude modulationPolarization mode dispersionTransmitterElectronic engineeringMultiplexingPhase-shift keyingFrequency offsetOpticsBit error rateAlgorithmChannel (broadcasting)TelecommunicationsOptical fiberSignal processingPhysicsEngineering

Abstract

fetched live from OpenAlex

We propose a decision-aided algorithm to compensate the sampling frequency offset (SFO) between the transmitter and receiver for reduced-guard-interval (RGI) coherent optical (CO) OFDM systems. In this paper, we first derive the cyclic prefix (CP) requirement for preventing OFDM symbols from SFO induced inter-symbol interference (ISI). Then we propose a new decision-aided SFO compensation (DA-SFOC) algorithm, which shows a high SFO tolerance and reduces the CP requirement. The performance of DA-SFOC is numerically investigated for various situations. Finally, the proposed algorithm is verified in a single channel 28 Gbaud polarization division multiplexing (PDM) RGI CO-OFDM experiment with QPSK, 8 QAM and 16 QAM modulation formats, respectively. Both numerical and experimental results show that the proposed DA-SFOC method is highly robust against the standard SFO in optical fiber transmission.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.468
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.030
GPT teacher head0.266
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it